Most large computing systems (e.g., an enterprise-wide computing system including a plurality of servers, data storage devices and the like) are built on a monolithic architecture model. In this regard, the computing systems are created as a service mesh; i.e., servers or the like are created/deployed and services/applications are installed on the servers by creating a service layer. Such deployment of additional computing resources may include, adding physical computing resources (e.g., servers, data storage devices or the like), or virtual use of the physical computing resources. Such virtual use may include deploying Virtual Machines (VMs) the physical computing resources and/or deploying operating system-level virtualization, such as containers. VMs provide for creating virtual kernels on physical computing resources, while containers create virtual application layers that run on a single kernel.
Such monolithic computing systems typically are not efficient in terms of computing resource utilization, since new services and/or a higher service demand typically result in deploying additional computing resources. While conventional virtual use of computing resources (e.g., VMs or containers) can be advantageous in terms of allocating resources based on service demand, such virtual use still requires resource usage (e.g., memory or processor/CPU) even after the service usage. Specifically, conventional virtual use, such as VMs, require deployment of an agent that remains in memory after the service has executed and, in some instances the agent that remains is running in a stand-by/sleep mode. Similarly, with use of containers, the container, and the agent deployed in the container, remain in memory after the service has executed. In such instances, the agent remains in the memory and may persist in a executing or stand-by mode in order for the agent to subsequently receive commands and execute as a response to the commands.
Therefore, a need exists to develop a computing system architecture that is highly elastic in nature so as to support on-demand use of computing resources for data processing operations based on the current and/or foreseen usage of the computing resources. In addition, a need exits to be able to implement a computing system architecture that is able to dynamically address increases in service demand without having to deploy additional computing resources, i.e., either additional physical resources and/or virtual resources. In this regard, a need exists to be able provide for virtual use of computing resources absent the need for agents, containers or the like that persist at the physical computing resource after the service is no longer running.